Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/67112
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorZhu, R-
dc.creatorGuilbert, E-
dc.creatorWong, MS-
dc.date.accessioned2017-05-22T02:29:31Z-
dc.date.available2017-05-22T02:29:31Z-
dc.identifier.issn2194-9042en_US
dc.identifier.urihttp://hdl.handle.net/10397/67112-
dc.description23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS), Commission II, 12–19 July 2016, Prague, Czech Republicen_US
dc.language.isoenen_US
dc.publisherCopernicus Publicationsen_US
dc.rights© Author(s) 2016. This work is distributed under the Creative Commons Attribution 3.0 License.en_US
dc.rightsThis publication Zhu, R., Guilbert, E., and Wong, M. S.: Tracking the spatial evolution of urban heat islands, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., 2016, III-2, 3-8, is available at https://doi.org/10.5194/isprs-annals-III-2-3-2016en_US
dc.subjectSpatiotemporal data modelingen_US
dc.subjectUrban heat islandsen_US
dc.subjectRemote sensingen_US
dc.titleTracking the spatial evolution of urban heat islandsen_US
dc.typeConference Paperen_US
dc.identifier.spage3en_US
dc.identifier.epage8en_US
dc.identifier.volumeIII-2en_US
dc.identifier.doi10.5194/isprsannals-III-2-3-2016en_US
dcterms.abstractThe urban heat island (UHI) phenomenon occurring in the urban areas or city-clusters is increasingly becoming a severe problem in the urbanization process. Previous research mainly rely on grid analysis techniques to study temperature data from images recorded at fixed time instants. The evolutionary process of UHI in both time and space has not been investigated yet. This research designs an object-oriented spatiotemporal model to reconstruct the evolution of UHI and provide a qualitative interpretation. Each UHI is modeled as a spatiotemporal field object with it own life cycle. Dynamic behavior of an UHI is defined by sequences of spatial changes (e.g. contraction or expansion) and topological transformations (e.g. merge or split). The model is implemented in an object-relational database and applied to air temperature data collected from weather stations every hour over three days. UHIs with their behavior were extracted from the data. Results suggest that the model can effectively track and provide a qualitative description of the UHI evolution.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationISPRS annals of the photogrammetry, remote sensing and spatial information sciences, 2016, v. III-2, p. 3-8-
dcterms.isPartOfISPRS annals of the photogrammetry, remote sensing and spatial information sciences-
dcterms.issued2016-
dc.identifier.isiWOS:000391012100001-
dc.identifier.ros2016002719-
dc.relation.conferenceInternational Society for Photogrammetry and Remote Sensing. Congress [ISPRS Congress]en_US
dc.identifier.eissn2194-9050en_US
dc.identifier.rosgroupid2016002663-
dc.description.ros2016-2017 > Academic research: refereed > Publication in refereed journalen_US
dc.description.validate201812_a bcmaen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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